In the quest for sustainable energy, nuclear fusion stands as a beacon of hope, promising virtually limitless power with minimal environmental impact. However, the path to harnessing this power is fraught with challenges, particularly in understanding and controlling the complex behavior of plasma within experimental reactors. A groundbreaking study led by Dr. R. Rossi from the Department of Industrial Engineering at the University of Rome ‘Tor Vergata’ is paving the way for more accurate and efficient plasma diagnostics, potentially revolutionizing the field of nuclear fusion.
The study, published in Nuclear Fusion, introduces a novel approach using Physics-Informed Neural Networks (PINNs) to enhance the accuracy of tomographic inversions from bolometer data. This method promises to significantly improve our ability to reconstruct and model the radiative patterns within tokamaks, the most widely used devices for magnetic confinement fusion.
Traditional diagnostic tools, such as magnetic probes and interferometers, provide only partial information about the plasma’s status. Bolometers, which measure radiation, offer valuable data but require complex inversion algorithms to extract meaningful local information. Rossi’s work addresses these challenges by leveraging the power of PINNs, which not only enhance the accuracy of these inversions but also offer advanced capabilities like super-resolution, data projection, and self-modelling.
“PINNs allow us to capture the intricate physics involved in radiative patterns more accurately than traditional methods,” Rossi explains. “This means we can better understand and control the plasma, which is crucial for advancing fusion research and bringing us closer to practical fusion power.”
The implications of this research are vast. By providing more precise and detailed information about plasma behavior, PINNs can help scientists better understand and mitigate phenomena like Edge Localized Modes (ELMs) and Multifaceted Asymmetric Radiation from the Edge (MARFE), which can disrupt the stability of the plasma. This enhanced understanding could lead to more efficient and stable fusion reactions, bringing us one step closer to commercial fusion power.
The study’s findings were first validated using synthetic cases and then applied to real-world scenarios at the Joint European Torus (JET), one of the world’s largest and most powerful tokamaks. The results were compelling, demonstrating the potential of PINNs to revolutionize plasma diagnostics.
“Our work shows that PINNs can provide significant benefits for both research and practical applications in nuclear fusion,” Rossi states. “This technology is not limited to tomography; it can tackle any kind of inverse problem, making it a versatile tool for advancing the field.”
As the energy sector continues to explore sustainable solutions, the development of more accurate and efficient diagnostic tools is crucial. Rossi’s research, published in Nuclear Fusion, offers a promising pathway forward, potentially accelerating the development of commercial fusion power and reshaping the future of energy production.
